8 results about "Pre analytical" patented technology

An analytical pretreatment method for analysis of samples includes: preparing an emulsion including oil, and a first droplet and a second droplet being present in the oil and containing a first sample and a second sample respectively; placing, on a substrate, an aggregate of the first droplet and the second droplet in the emulsion; and evaporating the oil and water on the substrate to separate a first evaporation residue and a second evaporation residue from each other that include the first sample and the second sample respectively.

The utility model discloses a water quality analysis pretreatment device which comprises a plurality of sample introduction passages, a sampling cup and an emptying valve, the sampling cup is connected with the plurality of sample introduction passages, and the bottom of the sampling cup is connected with the emptying valve; a valve A and a valve B in the sample introduction passage are connected, the NO end and the NC end of the valve A are respectively connected with a standard solution and a sample, and the NO end and the NC end of the valve B are respectively connected with an air compressor and a peristaltic pump A; the other end of the air compressor is externally connected with air, the other end of the peristaltic pump A is connected with a sampling cup through a valve C, the valve C and the sampling cup are connected with a peristaltic pump B through a three-way joint, and the other end of the peristaltic pump B is externally connected with pure water; the plurality of sample introduction channels are used for alternately introducing samples. According to the utility model, different dilution ratios of samples can be met, the flexibility of analysis pretreatment is improved, continuous sample introduction is realized, and the test efficiency is greatly improved.

In some embodiments, a method of creating a machine learning based automated authentication system for clinical laboratory diagnostics includes obtaining a biomarker training dataset including biomarker values for a plurality of biomarkers. The method also includes training the auto-encoder with the biomarker training data set as both an input and a target of the auto-encoder to create a trained auto-encoder. The method further includes deploying the trained auto-encoder in a hospital or laboratory. Numerous other embodiments are provided.

The application provides a precursor filling and sampling analysis system, and relates to the technical field of detection, comprising a collection module, a sampling and detection module and an analysis module. The collection module pre-processes the system pipeline and the container before obtaining the precursor, generates a pre-processing result, and obtains the precursor to be analyzed after meeting the preset conditions. The sampling and detection module detects the precursor to be analyzed online, generates a real-time heterogeneous data stream including first data of particulate matter information and second data of fluid state. The analysis module identifies and marks abnormal data points in the first data, constructs a causal association neighborhood based on the first data around the abnormal data points and the second data before the occurrence, extracts multi-dimensional physical features, and calculates a artifact confidence weight accordingly. When the confidence weight is higher than a preset threshold, the abnormal data points are reconstructed as baseline noise values, the real-time heterogeneous data stream is corrected, and a precursor quality analysis result is generated based on the corrected data.

Techniques disclosed herein can improve the extraction of chemicals prior to analysis by GC or GCMS. A liquid or solid sample can be placed in a sample container of a closed system under vacuum that further includes a sample extraction device. The assembly can be placed in a 3-zone heater that can separately control the temperature of the bottom of the sample container, the top of the sample container, and the sample extraction device. Vapor flux from the bottom of the sample container into the headspace of the sample container can deliver compounds of interest to the sample extraction device, whereas matrix compounds can re-condense in the headspace of the sample container to avoid delivery to the sample extraction device. Extraction can continue until substantial transfer of compounds of interest to the sorbent occurs, followed by thermal desorption of the extract into a GCMS for analysis.

A technique is provided that shortens the setup time for analytical methods by pretreating samples using SPE columns before analysis in the analytical unit. In the analytical system, a first flow path (21) includes one or more solid-phase separation columns. Samples from an autosampler (10) are introduced into either the first flow path (21) or the second flow path (22). The samples are then conveyed from either the first flow path (21) or the second flow path (22) via a switching valve (30) to the analytical column and detector (50) within the column oven (40). Sample purification is performed in the first flow path (21), while it is not performed in the second flow path (22).

1. The name of the design product: full-automatic nucleic acid detection analyzer. 2. The use of the design product: the design product is used for adding reagents and samples before analysis by clinical test analysis instrument, and amplification detection analysis of nucleic acid in clinical biological samples. 3. The design points of the design product: in shape. 4. The picture or photo that best indicates the design points: perspective view.

On the basis of characteristic information (21) indicating a relation between types of quantum gates used in a quantum circuit and simulation times in a DD quantum circuit simulator (30), an information processing apparatus (1) counts, for each qubit of the quantum circuit targeted, the numbers of quantum gates in descending order of simulation time. The information processing apparatus (1) then determines quantum gates with simulation time lengths at a predetermined rank or higher from plural types of quantum gates, determines the number of quantum gates for each quantum gate determined in a case where there are plural types of quantum gates determined to be at the predetermined rank or higher, rearranges an order of qubits to be provided to the quantum circuit simulator (30) in ascending order of the number determined, and outputs the rearranged order of the qubits. The information processing apparatus (1) thereby enables increase in speed of the simulation time of the DD quantum circuit simulator (30).